Patch-Clamp Recording Methods for Examining Adrenergic Regulation of Potassium Currents in Ocular Epithelial Cells
Bibliographic record
Abstract
Neurotransmitters act on cell-surface receptors to produce a wide range of effects on target cells ( 1 ). These effects include modulation of ion channels and changes in cellular electrical properties. Deciphering the intracellular molecular pathways by which receptor activation is transduced into alterations in cell function is often difficult owing to the accessibility to the cells to be studied in situ and the lack of regulation over both the extracellular and intracellular environment. The use of viable in vitro isolated cell models and patch-clamp recording methodology ( 2 ) to assay ion channel activity allows the identification of receptors and coupled intracellular signaling molecules, which regulate the response of interest. We have used whole-cell, patch-clamp recording techniques to study adrenergic receptor (AR) modulation of ion channels in ciliary epithelial cells ( 3 ). This approach has allowed us to measure current flowing via identified ion channels, and to identify the G-protein-coupled signaling pathway(s), which transduces AR activation to ion channel modulation. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".